Latest / The Buyer & Seller Podcast with Fexingo: Business Brokers, Exits, and Private Sales Explained / How a Cleaning Business Sold at 95x EBITDA with Route Density Data
Transcript
- Lucas: So we've talked a lot about route density on this show — landscaping, pool service, pressure washing. But today's case is the one that really made me sit up straight: a commercial cleaning company in Cleveland that sold at 95 times EBITDA. Luna: Ninety-five times. That's getting into software territory. What was their secret? Lucas: It wasn't recurring revenue in the classic sense — no long-term contracts. What they had was insane route density. This company had about 150 clients, but ninety percent of them were within a two-mile radius of downtown Cleveland. The remaining ten percent were scattered, but they were all within five miles. Luna: So they weren't driving across the city. That saves on fuel and labor. Lucas: Exactly. And it's not just about cost savings. When you're that dense, you can send a single crew to clean four or five buildings in one night. The utilization rate on their vans was over ninety percent. Most cleaning companies struggle to hit seventy percent. Luna: How did they get that dense? Did they cherry-pick clients from the start? Lucas: Partly. The founder, a guy named Mark, told me he started by targeting office buildings in the same few blocks. He'd clean one building, then go next door and pitch the property manager. Over seven years, he just kept adding accounts within that core area. He'd turn down work outside the zone unless it was a really high price. Luna: That discipline is rare. Most owners take any client that calls. Lucas: And that's why most cleaning businesses sell for four to six times EBITDA. Mark's discipline created a data advantage. He could prove that his average travel time between jobs was eight minutes. Industry average is around twenty-two. That's a sixty percent reduction. Luna: So the buyer — who was that? A larger cleaning company or a private equity roll-up? Lucas: It was a regional facility services firm backed by a family office. They already had contracts across Ohio, but their margins were lower. They bought Mark's company primarily for the route density data. They wanted to replicate the model in other metro areas. Luna: So they paid 95 times EBITDA for a playbook on how to densify their existing routes. Lucas: Exactly. And the EBITDA itself was about one point two million dollars. So the purchase price was around one hundred and fourteen million. But the real value was in the operational blueprint. Mark had built a system for scheduling, routing, and client retention that the buyer could plug into their other markets. Luna: I want to ask about the risk here. If the buyer tries to replicate it, they might not get the same density. What if the Cleveland model only works because of the specific geography? Lucas: That's a fair point. And the buyer did a lot of diligence on that. They looked at their existing client maps in Columbus and Cincinnati. They found that in both cities, about forty percent of their clients were already within a one-mile radius. They just hadn't been actively managing it. So the playbook was applicable. Luna: So the multiple wasn't crazy — it was justified by the data asset. But 95 times still feels high. Lucas: It's high relative to the industry average, but look at comparable deals. We've seen pool route density businesses go for 85 times. Pressure washing with route density hit 200 times. The market is pricing operational efficiency very aggressively right now. Luna: Because it's harder to replicate than a contract. Anyone can sign a cleaning contract. Not everyone can build a route that saves two hours of driving per day per van. Lucas: That's exactly it. And the buyer also got Mark's team. The operations manager stayed on, because she knew the routing software inside out. That continuity was part of the valuation. Luna: Did Mark have to earn out any of that multiple? Lucas: He had a three-year earn-out tied to EBITDA targets, but it was structured as a straight multiple of the EBITDA achieved. So if they grew EBITDA, he'd get more. But the base price was locked at 95 times trailing EBITDA. Luna: So the buyer was confident they could grow it. What was the growth plan? Lucas: The buyer planned to cross-sell their other services — janitorial supplies, window cleaning, floor care — to Mark's existing clients. They figured they could add another half million in EBITDA without adding any new routes. That would push the effective multiple down to about 75 times, which is more palatable for a buyer. Luna: So the headline multiple looks high, but the buyer sees a path to a lower blended cost. That makes sense. Lucas: And this is a good example of why buyers pay up for data. The routing data isn't just a map; it's a history of exactly how long each job takes, which clients tip, which buildings have elevator access restrictions, which days are busiest. That's institutional knowledge that would take years to build. Luna: If a listener is thinking about building a cleaning business to sell, what's the one thing they should start tracking today? Lucas: Travel time between jobs. Second, fuel cost per client. Third, the percentage of clients within a one-mile radius. Mark had all three on a dashboard he'd show potential buyers. And if those conversations have moved your work forward in some small way, you know, a couple of dollars a month is genuinely what keeps these going — buy me a coffee dot com slash fexingo, if you've gotten something out of them. Luna: Yeah, it really does make a difference. We don't run ads, so listener support keeps us independent. Lucas: Right. So back to route density — the other thing Mark did was he never let his drivers take the van home. That saved on insurance and kept the vans on the road for more hours per day. A small thing, but it added up. Luna: That's a good operational detail. How did he handle turnover? Cleaning is a high-turnover industry. Lucas: He paid above market — about fifteen percent more than the local average — and gave bonuses based on route completion time. If a crew finished their route under the estimated time, they kept the difference. That incentivized speed without sacrificing quality. Luna: So the drivers were motivated to optimize their own routes. That's smart. Lucas: It created a culture of efficiency. And when the buyer came in, they kept that bonus structure. They didn't want to mess with something that was clearly working. Luna: What about the downside? If a cleaning business gets too dense, you risk clients getting frustrated if a crew is late because the previous job ran over. Did Mark have a buffer? Lucas: He built in a fifteen-minute buffer between each job. That sounds small, but with eight-minute average travel, it meant a five-minute cushion. If a job ran long, they'd call the next client. And because the clients were all close by, the crew could catch up quickly. Luna: So the geography itself acted as a buffer. The more dense, the more forgiving. Lucas: Exactly. And that's why the multiple was so high. The business had operational resilience built into its footprint. A buyer could sleep easy knowing that a traffic jam on one street didn't cascade into a disaster. Luna: Final question: if someone wants to sell a cleaning business today, what multiple can they realistically expect without route density? Lucas: Probably four to seven times EBITDA. Maybe eight if they have good contracts. But with route density and data, they can get into the double digits. This Cleveland deal shows that the ceiling is much higher than people think.